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Data fabric, data lakehouse, and data mesh have emerged as viable alternatives to the modern data warehouse. These more recent architecture frameworks have solid benefits, but they're also surrounded by a lot of hyperbole and confusion. This course provides a guided tour of each architecture to help data professionals understand the pros and cons.
The course begins with a review of common data architecture concepts and the traditional data warehouse including its evolution into the modern data warehouse. Then we’ll take a detailed look at the rise of data fabrics for seamless data integration and access. Next, we will cover the data lakehouse architecture that combines the best features of data lakes and data warehouses. Lastly, we will study the data mesh, a decentralized data architecture that treats data as a product.
We will delve into the fundamentals of each of these architectures, discussing their structure, use-cases, benefits, and challenges. We will explore how they fit into different business scenarios, their suitability for diverse data types, and the strategies used for their implementation and management.
By the end of the course, students will have a clear understanding of which data architecture frameworks are best suited for specific business needs and how to implement them effectively to ensure data integrity, availability, and usability.
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You will learn:
- Concepts that provide working understanding of several data architectures
- The pros and cons of each approach
- How to distinguish data architecture theory from reality
- How to pick the best architecture for your use case
- The differences between data warehouses and data lakes
- Common data architecture concepts to help you build better solutions
- The historical evolution and characteristics of data architectures
This course is geared towards:
- Practicing and aspiring data architects
- CDOs, CIOs, and other executives with a role in defining data strategy
- Enterprise, analytics, and technology architects who work with data architects
- Data engineers, application designers and developers, data system designers and developers, and others who apply data architecture
- Anyone who needs to collaborate with data architects, and everyone with an interest in data architecture
Module 0. About the Course (2 min)
Module 1. Big Data and Data Architectures (23 min)
- Big Data
- Data Architectures
Module 2. Common Data Architecture Concepts (85 min)
- Relational Data Warehouse (RDW)
- Data Lake
- Data Storage Solutions
- Approaches to Design
- Approaches to Data Modeling
- Approaches to Data Ingestion
Module 3. Modern Data Warehouse (24 min)
- MDM Architecture
- Stepping Stones to the MDW
Module 4. Data Fabric (14 min)
- What is Data Fabric? – Part 1
- What is Data Fabric? – Part 2
- Data Fabric High-level Architecture
- Why Data Fabric?
- Data Fabric Drawbacks
- Data Fabric Architecture
- Intelligent Data Fabric
Module 5. Data Lakehouse (20 min)
- Data Lakehouse Historical Timeline
- Data Lake: Part 1
- Data Lake: Part 2
- Data Lakehouse High-level Architecture
- Use Cases for Data Lakehouse
- Data Lakehouse Architecture
- Data Lakehouse Needs a Relational Serving Layer
- Concerns Skipping Relational Data Warehouse: Part 1
- Concerns Skipping Relational Data Warehouse: Part 2
Module 6. Data Mesh Foundation (41 min)
- Data Mesh Foundation
- Data Mesh Foundation cont.
Module 7. Should You Adopt a Data Mesh (25 min)
- Data Mesh Myths
- Data Mesh Myths: Example
- Data Mesh Concerns
- Common Data Mesh Exceptions: Part 1?
- Common Data Mesh Exceptions: Part 2
- Should You Adopt a Data Mesh?
- Keys for a Successful Data Mesh
- Data Mesh Future: Part 1
- Data Mesh Future: Part 2
- When to Use Each Architecture?
- Contact Info
Click
- here - to download a more detailed outline of this course.
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This exam tests knowledge and understanding of basic concepts, principles, and terminology of analytics.
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You will be tested in these areas:
- Big data and data architecture
- Common characteristics of data architectures
- Relational data warehouse concepts
- Data lake concepts
- Data storage, data modeling, and data integration concepts
- Modern Data Warehouse architecture concepts, uses cases, and pros & cons
- Data Fabric architecture concepts, uses cases, and pros & cons
- Data Lakehouse architecture concepts, uses cases, and pros & cons
- Data Mesh architecture concepts, uses cases, and pros & cons
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Additional Information
Number of Questions: 24
Time Limit: 48 minutes
Passing Score: 70%
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Once you pass the exam, you will receive a Certificate of Education
documenting that you have demonstrated mastery of the topic. Course
exams count towards eLC certification programs. Visit our
Certification page for more information about our various programs.
We recommend that you take detailed notes and review the course material multiple times before taking this exam.
Click here to learn more about CIMP exams.
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